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A Factorial Dual-Interval Programming Approach for Planning Municipal Waste Management Systems

机译:规划城市垃圾管理系统的因子双间隔编程方法

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摘要

In this study, a factorial dual-interval programming (FDIP) approach is proposed through integrating factorial analysis and dual-interval linear programming into a general framework. The developed FDIP approach can handle uncertainties (i.e.,single-interval and dual-interval) that exist in the left-hand side and right-hand side of the system objective function and in the associated constraints. Moreover, it has the advantages in identifying significant parameters along with their joint effects on the system outputs. A case study of municipal solid waste (MSW) management is adopted to demonstrate the applicability of the proposed approach. Reasonable results have been generated for the waste flow allocation schemes with minimized system costs; impact factors and their interactive effects have been identified and analyzed for the lower bound and upper bound of the system outputs under various scenarios. It is indicated that the effect of operational costs of the waste-to-energy (WTE) facility during the first period is most influential and positive to the system costs; such operation costs have a slightly larger effect on the lower bound of the system costs than that on the upper bound of the system costs, providing valuable information when it comes to decision making.
机译:在这项研究中,通过将阶乘分析和双区间线性规划集成到一个通用框架中,提出了阶乘双区间规划(FDIP)方法。发达的FDIP方法可以处理系统目标函数左侧和右侧以及相关约束中存在的不确定性(即单间隔和双间隔)。此外,它在识别重要参数及其对系统输出的联合影响方面具有优势。通过对城市固体废物(MSW)管理进行案例研究,证明了该方法的适用性。废物流分配方案产生了合理的结果,系统成本降到最低;对于各种情况下系统输出的下限和上限,已经确定并分析了影响因素及其交互作用。研究表明,第一阶段的垃圾发电设施的运营成本影响最大,并且对系统成本有积极影响;这样的运营成本对系统成本下限的影响要比对系统成本上限的影响稍大,从而在决策时提供了有价值的信息。

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